1. Technical Field
The present invention relates to collision avoidance systems adapted for use with a vehicle, and more particularly to an improved system configured to predict a projected path of a host vehicle, and detect a collision between the host vehicle and at least one other object.
2. Background Art
Collision control systems have been developed to reduce the likelihood of collisions between transportation machines, such as boats, aircrafts, and automotive vehicles. With respect to vehicles, these conventional safety applications rely upon the ability to determine the accurate relative positioning and predictable driving trajectories of the host and the surrounding vehicles to provide forward collision warning and effect automated braking in certain instances. In general, to identify the target vehicles that pose collision threats, current state of the art approaches use inputs from a variety of external vehicle sensors that detect surrounding vehicles and other objects. These sensory inputs are then utilized by a controller to determine a projected collision.
Though commonly used, these multi-sensor based systems present general concerns and inefficiencies. For example, to provide three-hundred-and-sixty degree detection numerous sensors are required, which significantly increase the total product and repair costs of the host vehicle. The numerous sensors are unreliable due to the extra complexity involved in interpreting and fusing sensory inputs in the final decision making algorithms. Further, the complexity of these conventional systems increases labor costs associated with training, manufacture, and design.
These systems are limited operationally due to inflexible vehicle-specific configurations. Of primary concern, these systems are limited by the capabilities of the sensors. For example, a rapidly approaching vehicle outside of the range of the applicable sensor(s) may collide with the host vehicle for lack of detection outside of a sufficient period from impact. Proper sensory performance is also affected by increasingly complex and over-burdened vehicle communication networks. In this instance, each separately performing sensor that presents an electrical control unit utilizes available bandwidth for inter-nodal communication. Where baud rates or capacity becomes insufficient, backlogging of sensory inputs may cause poor performance or the failure of the conventional system.
Finally, collision control systems are also limited in their ability to predict the future driving path of the host vehicle. In this regard, yaw-rate and steering angle sensors are conventionally used to predict the future path of the vehicle by assuming that the vehicle will undergo, for the immediate future, the same change in heading as is currently being commanded. The predictive capabilities of these systems, however, are limited by the ability of the operator to minimize steering angle and heading oscillations, which cause the predicted path to change dramatically. Further, the driving path of the vehicle often follows the shape of the roadway. For this reason, many systems attempt to identify the roadway or lane shape to perform path prediction, and often employ map databases and vision systems for this purpose. However, map systems are expensive, and vision systems may have trouble overcoming challenging environmental conditions due to limited views of the roadway.